Water Distribution Network Models - Construction & Maintenance
Network Modelling Expertise
STRUMAP / HARP
HydroCo are considered leaders in the field of network modelling; a reputation that is built on the premise of producing high quality network models that offer great value for money. Our highly trained staff have a wealth of experience using all the major modelling software packages. With over 20 years experience in building hydraulic network models, we understand the intricacies of modelling inside and out, ensuring a robust model, suitable for all its potential applications in the future.
" .. HydroCo are experts in the all major modelling packages .."
We have developed many additional tools to enable experienced staff to rapidly build strategic or detailed ‘all mains’ models using your geographic information system and customer data. Our data integration specialists fully understand the issues involved in importing and exporting a wide variety of data from different company systems into various modelling packages.
Building your network model
What is a water network model? In layman's terms, a model is a geographical and hydraulic representation of a potable water distribution system on a computer, that can be used to simulate how the system operates over a given time period. This can be used as a planning tool, testing different scenarios on a computer, without any impact on the customer. Because of this, models are often used to minimise 'risk' for a water company. Without a model, mistakes may cost the company far more than the model costs to build.
".. models reduce risk and quantify the impact of system changes .."
Before building your network model, you need to consider all the possible applications for it after its completion. Network models are no longer only used by a privileged few; with minimal training, their application can be applied across your whole business, from small scale operational decisions and emergency planning, right through to long term strategic planning and technical submissions to the regulator. The application drives the level of information used in its construction and the detail required for field testing and calibration. Please review our model applications / case study pages for inspiration.
The accuracy of a network model is directly proportionate to the quality of the data you use to construct it; HydroCo spend a considerable amount of time analysing and preparing the data that is to be used in a model build to ensure it is fit for purpose. The foundations for a model are typically constructed using data from your Geographical Information System (GIS), providing the basis for pipe length, material, connectivity etc. This process has been streamlined over the years using our in house bespoke software applications, designed to maximise the accuracy of the data, whilst minimising the cost of data cleansing to our clients.
Modelling your customer's water consumption can be achieved by using a variety of techniques. In recent years we have been tying customer locations and billing records to pipes to bring increasingly more realism to your models. HydroCo have developed many bespoke technical routines to convert your customer billing information into your preferred modelling format and apply these demands to the correct places within your network.
The last 10 - 15 year period has seen the growth of the use of telemetry systems at the heart of a water companies corporate data systems - this data is invaluable to a network model builder, since it reduces field work costs and improves the accuracy of demand allocation during the models construction.
With all the elements that go into building a model brought together to form a 'base model', it is time to bring some realism into your model through calibration. This is traditionally achieved by the collection of field data from your water network, where data is monitored over a period of a week. This data is then validated and collated, before being imported into the modelling environment for comparison. The variables within the network model are then adjusted to reflect the 'live' data, which in turn represents the real system.
Many people consider this the end of the process - however, the model build process typically identifies a whole raft of unexpected anomalies within your water supply system. If these anomalies are addressed, the operational efficiency of the system is typically improved with significant long term cost benefits. There is rarely such an opportunity to assess a system in such great detail, bringing additional benefits to the water company.
The accuracy of your model depends on how closely it reflects your systems current configuration - your water network is constantly being changed and modified to best serve the needs of your customers. With valve status, pump control and other operational changes, to new developments, mains rehabilitation and major capital schemes coming on line it is important that your model is modified to reflect these changes. A model slowly becomes outdated, and its ability to predict the correct answers is then compromised. To overcome these issues, some water companies choose to regularly rebuild their models; however, this can become very expensive. A more cost effective approach is to maintain your models, extending their lifespan and getting more value from your original investment.
".. model maintenance helps maximise your original investment, by ensuring a long model life span.. "
It is difficult to judge when a model needs to be updated - HydroCo offer a model verification service, using either telemetry or field data to compare your model results to the actual system and assess whether an update is necessary. This can be a largely automated process, allowing larger companies to measure their whole model stock at regular intervals to determine which ones require further investment.
HydroCo have a series of cost effective techniques designed to consider every single aspect of system change that might have an impact on your model. We have developed tools that can compare your corporate data systems to your network models and identify where changes exist. The subsequent differences can then be applied to your models.
An updated model can be compared against the old model results and the performance of the actual system to gauge the validity of the changes.